computer architecture and embedded system
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Embedded SystemsIntroduction
L1
References
1. Embedded Systems Design, Steve Heath, Elsevier
2. Embedded Systems Design, Frank Vahid & Tony Givargis, John wiley
3. Fundamentals of embedded software, Daniel W lewis, Pearson education
4. Embedded Microcomputer Systems, Jonathan W Valavano, Brooks/cole, Thomson Learning
5. Embedded Systems Design, Oliver Bailey, Dreamtech
6. Embedded Real-time Systems, K V K K Prasad, Dreamtech
Outline
• Embedded systems overview– What are they?
• Design challenge – optimizing design metrics
• Technologies– Processor technologies
– IC technologies
– Design technologies
Embedded systems overview
• When we talk of microprocessors we think of computers as they are everywhere
• Computers often mean – Desktop PC’s– Laptops– Mainframes– Servers
• But there’s yet another type of computing system– Far more common...
Embedded systems overview
• Embedded computing systems– (Micro)processors are
embedded within electronic devices, equipment, appliances
– Hard to define - any computing system other than a desktop computer
– Billions of units produced yearly, versus millions of desktop units
– Perhaps 50 per household and per automobile
Computers/ microprocessors are in here...
Many times more processors used in
each of them , though they cost
much lessThese processors make these devices
sophisticated, versatile and inexpensive
Toys, mobile phones, kitchen appliances,
even pens
A “short list” of embedded systems
And the list goes on and on
Anti-lock brakesAuto-focus camerasAutomatic teller machinesAutomatic toll systemsAutomatic transmissionAvionic systemsBattery chargersCamcordersCell phonesCell-phone base stationsCordless phonesCruise controlCurbside check-in systemsDigital camerasDisk drivesElectronic card readersElectronic instrumentsElectronic toys/gamesFactory controlFax machinesFingerprint identifiersHome security systemsLife-support systemsMedical testing systems
ModemsMPEG decodersNetwork cardsNetwork switches/routersOn-board navigationPagersPhotocopiersPoint-of-sale systemsPortable video gamesPrintersSatellite phonesScannersSmart ovens/dishwashersSpeech recognizersStereo systemsTeleconferencing systemsTelevisionsTemperature controllersTheft tracking systemsTV set-top boxesVCR’s, DVD playersVideo game consolesVideo phonesWashers and dryers
Embedded systems
A microprocessor based system that is built to control a function(s) of a system and is designed not to be programmed by the user. (controller)
User could select the functionality but cannot define the functionality.
Embedded system is designed to perform one or limited number of functions, may be with choices or options.
PCs provide easily accessible methodologies, HW & SW that are used to build Embedded systems
Why did they become popular?
Replacement for discrete logic-based circuits
Functional upgradability ?, easy maintenance upgrades
Improves the performance of mechanical systems through close control
Protection of Intellectual property
Replacement of Analogue circuits (DSPs)
What does an Embedded system consist of?
Processor – Types, technologies, functionalities
Memory – how much, what types, organisation
Peripherals/ I/O interfaces – communicate with the user, external environment
Inputs and outputs / sensors & actuators – Digital - binary, serial/parallel, Analogue, Displays and alarms, Timing devices
SW – OS, application SW, initialisation, self check
Algorithms
Path of electronic design
Mechanical control systems- expensive & bulky
Discrete electronic circuits – fast but no flexibility
SW controlled circuits – microprocessors and controllers – slow, flexible
HW implementation of SW, HW & SW systems
Some Common Characteristics of Embedded Systems
• Single-functioned– Executes a single program, repeatedly
• Tightly-constrained– Low cost, low power, small, fast, etc.
• Reactive and real-time– Continually reacts to changes in the system’s
environment– Must compute certain results in real-time
without delay
Embedded system - digital camera
Microcontroller
CCD preprocessor Pixel coprocessorA2D
D2A
JPEG codec
DMA controller
Memory controller ISA bus interface UART LCD ctrl
Display ctrl
Multiplier/Accum
Digital camera chip
lens
CCD
• Single-functioned -- always a digital camera
• Tightly-constrained -- Low cost, low power, small, fast
• Reactive and real-time -- only to a small extent
Design challenge – optimizing design metrics
• Obvious design goal:– Construct an implementation with desired
functionality• Key design challenge:
– Simultaneously optimize numerous design metrics
• Design metric– A measurable feature of a system’s
implementation– Optimizing design metrics is a key challenge
Design challenge – optimizing design metrics
• Common metrics– Unit cost: the monetary cost of manufacturing each
copy of the system, excluding NRE cost
– NRE cost (Non-Recurring Engineering cost): The one-time monetary cost of designing the system
– Size: the physical space required by the system
– Performance: the execution time or throughput of the system
– Power: amount of power consumed by the system
– Flexibility: the ability to change the functionality of the system without incurring heavy NRE cost
Design challenge – optimizing design metrics
• Common metrics (continued)
– Time-to-prototype: the time needed to build a working version of the system
– Time-to-market: the time required to develop a system to the point that it can be released and sold to customers
– Maintainability: the ability to modify the system after its initial release
– Correctness, safety, many more
Design metric competition -- improving one may worsen others
• Expertise with both software and hardware is needed to optimize design metrics– A designer must be
comfortable with various technologies in order to choose the best for a given application and constraints
SizePerformance
Power
NRE cost
Microcontroller
CCD preprocessor Pixel coprocessorA2D
D2A
JPEG codec
DMA controller
Memory controller ISA bus interface UART LCD ctrl
Display ctrl
Multiplier/Accum
Digital camera chipCCD
Hardware
Software
Time-to-market: a demanding design metric
• Time required to develop a product to the point it can be sold to customers
• Market window– Period during which the
product would have highest sales
• Average time-to-market constraint is about 8 months
• Delays can be costly
Revenue
Time (months)
Losses Due to Delayed Market Entry
• Simplified revenue model– Product life = 2W, peak
at W– Time of market entry
defines a triangle, representing market penetration
– Triangle area equals revenue
• Loss – The difference between
the on-time and delayed triangle areas
On-time Delayedentry entry
Peak revenue
Peak revenue from delayed entry
Market rise
Market fall
W 2W
Time
D
On-time
Delayed
Rev
enu
es (
$)
Losses due to delayed market entry (cont.)• Area = 1/2 * base * height
– On-time = 1/2 * 2W * W
– Delayed = 1/2 * (W-D+W)*(W-D)
• Percentage revenue loss =
(D(3W-D)/2W2)*100%
• Try some examples
– Lifetime 2W=52 wks, delay D=4 wks
– (4*(3*26 –4)/2*26^2) = 22%
– Lifetime 2W=52 wks, delay D=10 wks
– (10*(3*26 –10)/2*26^2) = 50%
– Delays are costly!
On-time Delayedentry entry
Peak revenue
Peak revenue from delayed entry
Market rise
Market fall
W 2W
Time
D
On-time
Delayed
Rev
enu
es (
$)
NRE and Unit Cost Metrics
• Costs:– Unit cost: the monetary cost of manufacturing each copy of the
system, excluding NRE cost
– NRE cost (Non-Recurring Engineering cost): The one-time monetary cost of designing the system
– total cost = NRE cost + unit cost * # of units
– per-product cost = total cost / # of units
= (NRE cost / # of units) + unit cost
• Example– NRE= Rs 20000, unit= Rs100– For 100 units
– total cost = 20000 + 100*100 = 30000– per-product cost = 30,000/100 or 20000/100 + 100 = 300
Amortizing NRE cost over the units results in an additional Rs 200 per
unit
NRE and unit cost metrics
• Compare technologies by costs -- best depends on quantity !– Technology A: NRE=Rs 5,000, unit=Rs
100
– Technology B: NRE=Rs 1,00,000, unit=Rs 25
– Technology C: NRE=Rs10,00,000, unit= Rs 2
The performance design metric• Widely-used measure of system, widely-abused
– Clock freq, instructions per second – not good measures– Digital camera example – a user cares about how fast it
processes images, not clock speed or instructions per second• Latency (response time)
– Time between task start and end– e.g., Camera’s A and B process images in 0.25 & 0.3 seconds
• Throughput– Tasks per second, e.g. Camera A processes 4 images & B say
8 images per second– Throughput can be more than latency seems to imply due to
concurrency, (by capturing a new image while previous image is being stored).
• Speedup of B over S = B’s performance / A’s performance– Throughput speedup = 8/4 = 2
Three key embedded system technologies
• Technology– A manner of accomplishing a task,
especially using technical processes, methods, or knowledge
• Three key technologies for embedded systems– Processor technology– IC technology– Design technology
Processor technology• The architecture of the computation engine used to
implement a system’s desired functionality• Processor does not have to be programmable
– “Processor” not equal to general-purpose processor
Application-specific
Single-purpose (“hardware”)
Registers
CustomALU
DatapathController
Program memory
Assembly code for:
total = 0 for i =1 to …
Control logic and
State register
Datamemory
IR PC
DatapathController
Control logic
State register
Datamemory
index
total
+
IR PC
Registerfile
GeneralALU
DatapathController
Program memory
Assembly code for:
total = 0 for i =1 to …
Control logic and
State register
Datamemory
General-purpose (“software”)
Processor technology• Processors vary in their customization for the problem at
hand
total = 0for i = 1 to N loop total += M[i]end loop
General-purpose
processor
Single-purpose processor
Application-specific
processor
Desired functionality
General-purpose processors
• Programmable device used in a variety of applications– Also known as “microprocessor”
• Features– Program memory– General datapath with large register
set and general ALU
• User benefits– Low time-to-market and NRE costs– High flexibility
• “Pentium” the most well-known, but there are hundreds of others
IR PC
Registerfile
GeneralALU
Data pathController
Program memory
Assembly code for:
total = 0 for i =1 to …
Control logic and
State register
Datamemory
Single-purpose processors
• Digital circuit designed to execute exactly one program– Ex. coprocessor, accelerator Features– Contains only the components
needed to execute a single program
– No program memory
• Benefits– Fast– Low power– Small size
DatapathControllerControl logic
State register
Datamemory
index
total
+
Application-specific Instruction set Processors• Programmable processor
optimized for a particular class of applications having common characteristics– Compromise between general-
purpose and single-purpose processors
• Features– Program memory– Optimized datapath– Special functional units
• Benefits– Some flexibility, good performance,
size and power
IR PC
Registers
CustomALU
DatapathController
Program memory
Assembly code for:
total = 0 for i =1 to …
Control logic and
State register
Datamemory
IC technology
• The manner in which a digital (gate-level) implementation is mapped onto an IC– IC: Integrated circuit, or “chip”– IC technologies differ in their customization to a
design– IC’s consist of numerous layers (perhaps 10 or
more)• IC technologies differ with respect to who builds each
layer & when
source drainchannel
oxide
gate
Silicon substrate
IC package
IC
IC technology
• Three types of IC technologies– Full-custom/VLSI
– Semi-custom ASIC (gate array and standard cell)
– PLD (Programmable Logic Device)
Full-custom/VLSI
• All layers are optimized for an embedded system’s particular digital implementation– Placing transistors– Sizing transistors– Routing wires
• Benefits– Excellent performance, small size, low power
• Drawbacks– High NRE cost (e.g., Rs 2 M), long time-to-market
Semi-custom
• Lower layers are fully or partially built– Designers are left with routing of wires and
maybe placing some blocks
• Benefits– Good performance, good size, less NRE
cost than a full-custom implementation (perhaps $10k to $100k)
• Drawbacks– Still require weeks to months to develop
PLD (Programmable Logic Device)
• All layers already exist– Designers can purchase an IC– Connections on the IC are either created or
destroyed to implement desired functionality– Field-Programmable Gate Array (FPGA) very
popular
• Benefits– Low NRE costs, almost instant IC availability
• Drawbacks– Bigger, expensive (perhaps Rs 2000 per unit),
power hungry, slower
Moore’s law• The most important trend in embedded systems
– Predicted in 1965 by Intel co-founder Gordon Moore
IC transistor capacity has doubled roughly every 18 months for the past several decades
10,000
1,000
100
10
10.1
0.01
0.001
Log
ic
tran
sist
ors
per
chip
(in
mil
lion
s)
1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009
Note: logarithmic
scale
Moore’s law
– This growth rate is hard to imagine, most people underestimate
Graphical illustration of Moore’s law
1981 1984 1987 1990 1993 1996 1999 2002
Leading edgechip in 1981
10,000transistors
Leading edgechip in 2002
150,000,000transistors
• Something that doubles frequently grows more quickly than most people realize!– A 2002 chip can hold about 15,000 1981 chips inside itself
Design of Embedded Systems (Wescon 1975)
• “... avoid data processing aides such as assemblers, high-level languages, simulated systems, and control panels. These computer-aided design tools generally get in the way of cost-effective design and are more a result of the cultural influence of data processing, rather than a practical need.”
• “bulk of real-world control problems require less than 2,000 instructions to implement. For this size of program computer aided design does little to improve the design approach and does a lot to separate the design engineer from intimate knowledge of his hardware.”
Design needs Design technology
Achieving the metrics + fast & reliably
Enhanced productivity
Design – single stage
Multi stage - several abstraction levels
Design Technology• The manner in which we convert our concept of
desired system functionality into an implementation
Libraries/IP: Incorporates pre-designed implementation from lower abstraction level into higher level.
Systemspecification
Behavioralspecification
RTspecification
Logicspecification
To final implementation
Compilation/Synthesis: Automates exploration and insertion of implementation details for lower level.
Test/Verification: Ensures correct functionality at each level, thus reducing costly iterations between levels.
Compilation/Synthesis
Libraries/IP
Test/Verification
Systemsynthesis
Behaviorsynthesis
RTsynthesis
Logicsynthesis
Hw/Sw/OS
Cores
RTcomponents
Gates/Cells
Model simulat./checkers
Hw-Swcosimulators
HDL simulators
Gate simulators
Compilation and synthesis
Specify in abstract manner and get lower level details
Libraries and IP - reusability
Are ICs a form of libraries?
How do cores differ from ICs
Test / verification
Simulation
HDL based simulations
System
User I/F or Operator perspective
Functionality perspective
Architectural perspective
Multiple perspectives for visualisation of a system
Physical
Environmental
Performance
Systematic Design of Embedded Systems• Most embedded systems are far too complex for
Adhoc/empirical approach to design(100,000 lines) • Methodical, engineering-oriented, tool-based
approach is essential– specification, synthesis, optimization,
verification etc.– prevalent for hardware, still rare for software
• One key aspect is the creation of models– Representation of knowledge and ideas about
the system being developed - specification– Models only represent certain properties to be
analyzed, understood & verified. They omit or modify certain details (abstraction) based on certain assumptions. One of the few tools available for dealing with complexity
Abstractions and Models• Models are foundations of science and engineering• Designs usually start with informal specifications• However, soon a need for Models and Abstractions
is established• Models or abstractions have connections to
Implementation (h/w, s/w) and Application• Two types of modeling: System structure & system
behavior– The relationships, behavior and interaction of
atomic components– Coordinate computation of & communication
between components • Models from classical CS
– FSM, RAM (von Neumann), CCS (Milner)– Turing machine, Universal Register Machine
Models
Conceptual model
Physical model
Analogue model
Mathematical model
Numerical model
Computational model
Implementation
Assumptions & accuracy
Good Models• Simple
– Ptolemy vs. Galileo• Amenable for development of theory to reason
– should not be too general• Has High Expressive Power
– a game is interesting only if it has some level of difficulty!
• Provides Ability for Critical Reasoning– Science vs. Religion
• Practice is currently THE only serious test of model quality
• Executable (for Simulation)• Synthesizable• Unbiased towards any specific implementation (h/w
or s/w)
Modeling Embedded Systems
• Functional behavior: what does the system do– in non-embedded systems, this is sufficient
• Contract with the physical world– Time: meet temporal contract with the environment
• temporal behavior important in real-time systems, as most embedded systems are
• simple metric such as throughput, latency, jitter• more sophisticated quality-of-service metrics
– Power: meet constraint on power consumption• peak power, average power, system lifetime
– Others: size, weight, heat, temperature, reliability etcSystem model must support description of both
functional behavior and physical interaction
Elements of a Model of a Computation System: Language
• Set of symbols with superimposed syntax & semantics– textual (e.g. matlab), visual (e.g. labview) etc.
• Syntax: rules for combining symbols– well structured, intuitive
• Semantics: rules for assigning meaning to symbols and combinations of symbols– without rigorous semantics, precise model behavior
over time is not well defined– full executability and automatic h/w or s/w
synthesis is impossible– E.g. operational semantics (in terms of actions of an
abstract machine), denotational semantics (in terms of relations)
Simulation and Synthesis
• Two sides of the same coin• Simulation: scheduling then execution on desktop
computer(s)• Synthesis: scheduling then code generation in C++, C,
assembly, VHDL, etc.• Validation by simulation important throughout
design flow• Models of computation enable
– Global optimization of computation and communication
– Scheduling and communication that is correct by construction
Models Useful In Validating Designs• By construction
– property is inherent.• By verification
– property is provable.• By simulation
– check behavior for all inputs.• By intuition
– property is true. I just know it is.• By assertion
– property is true. Would make something of it?• By intimidation
– Don’t even try to doubt whether it is true
It is generally better to be higher in this list !
An embedded system is expected to receive inputs, process data or information, and provide outputs
The processing is done by processors
Before we build the processor we must know the expected behaviour of the processor
This is the model of the processor. We may call it a computational model. Before the processor is built it is in our mind. We express this model through a description - text, graphics, or some formal language
Models & Languages
Models exist without languageModels are expressed in some language or the other A model could be expressed in different languagesA language could express more than one modelSome languages are better suited to express some models
Types of models – many & include
Sequential model – A model that represents the embedded system as a sequence of actions. A variety of systems need this sequence of steps. Most programming languages and natural languages can express this featureCommunicating-process model – A number of independent processes (may be sequential) communicate among themselves whilst doing their job. Synchronisation/signalling, passing data, mutual exclusion etc. Some languages are better suited.
State machine model – A model where the embedded system resides in a state till an input to the system/event makes it change its state. Most reactive and control system applications fall under this category. FSM representations are good way expressing the model. Text Vs Graphic languagesData flow model – An embedded system that functions mainly by transforming an input data stream into an output data stream – functioning of an mpeg camera – UML may be more useful. Most DSP applications
OO models – Well known – Useful for successive decomposition problems, problems where OO paradigm is useful etc.
Multiple models and multiple languages may be needed to describe a complex system.
The model description must be accompanied by semantic descriptions for proper processing
Lift model - English language description Lift cage contains a number of controls – floor numbers, open and close door, it receives the data regarding the floor it is at. Users press the floor number to which they desire to go and depending upon the current location and the floor it has to go it moves up and down. Before it moves, the door is closed. On reaching the floor it keeps the door open for 15 sec, unless close door operation is executed before door closes. When stationary, door is kept closed. When moving in a direction it does not return to opposite direction, even on request, unless no request for higher or lower floor in the same direction is pending
Problems1. Develop a model for the lift controller 2. Identify one problem each that fits into the
models discussed above.3. Develop a model for a data acquisition
system that receives data from 14 channels through A/D converters and takes appropriate control actions as a function of the 14 inputs and communicates with 4 actuators. Inputs from channel 15 or 16 need immediate response, and the controller must respond in a time of about 20 clock cycles. In these cases, actuator 5 is activated.
Modeling Approaches based on Software Design Methods
• No systematic design in 60s• From 70s, many different s/w design strategies
– Design methods based on functional decomposition• Real-Time Structured Analysis and
Design(RTSAD)– Design methods based on concurrent task
structuring• Design Approach for Real-Time Systems
(DARTS)– Design methods based on information hiding
• Object-Oriented Design method (OOD)– Design methods based on modeling the domain
• Jackson System Development method (JSD)• Object-Oriented Design method (OOD)
continued
• UML is the latest manifestation– becoming prevalent in complex embedded
system design
How Models Influence an Application Design?
• Example: given input from a camera, digitally encode it using MPEG II encoding standards.
• this task involves: storing the image for processing going through a number of processing steps, e.g., Discrete cosine transform (DCT), Quantization, encoding (variable length encoding), formatting the bit stream, Inverse Discrete Cosine transform (IDCT), ...
• Is this problem appropriate for• Reactive Systems, Synchronous Data flow,
CSP, ...• More than one model could be appropriate.
Choice of Model
• Model Choice: depends on– application domain
• DSP applications use data flow models• Control applications use finite state machine
models• Event driven applications use reactive models
– efficiency of the model• in terms of simulation time• in terms of synthesized circuit/code.
• Language Choice: depends on– underlying semantics
• semantics in the model appropriate for the application.
– available tools– personal taste and/or company policy
Design productivity exponential increase
• Exponential increase over the past few decades
100,000
10,000
1,000
100
10
1
0.1
0.01
19831981 1987 1989 1991 19931985 1995 1997 1999 2001 2003 2005 2007 2009
Productivity(K) Trans./Staff – Mo.
The co-design ladder
• In the past:– Hardware and software
design technologies were very different
– Recent maturation of synthesis enables a unified view of hardware and software
• Hardware/software “codesign”
Implementation
Assembly instructions
Machine instructions
Register transfers
Compilers(1960's,1970's)
Assemblers, linkers(1950's, 1960's)
Behavioral synthesis(1990's)
RT synthesis(1980's, 1990's)
Logic synthesis(1970's, 1980's)
Microprocessor plus program bits: “software”
VLSI, ASIC, or PLD implementation: “hardware”
Logic gates
Logic equations / FSM's
Sequential program code (e.g., C, VHDL)
The choice of hardware versus software for a particular function is simply a tradeoff among various design metrics, like performance, power, size, NRE cost,
and especially flexibility; there is no fundamental difference between what hardware or software can implement.
Independence of Processor and IC Technologies
• Basic tradeoff– General vs. custom
– With respect to processor technology or IC technology
– The two technologies are independent
General-purpose
processor
ASIPSingle-
purposeprocessor
Semi-customPLD Full-custom
General,providing improved:
Customized, providing improved:
Power efficiencyPerformance
SizeCost (high volume)
FlexibilityMaintainability
NRE costTime- to-prototype
Time-to-marketCost (low volume)
Design productivity gap
• While designer productivity has grown at an impressive rate over the past decades, the rate of improvement has not kept pace with chip capacity
10,000
1,000
100
10
1
0.1
0.01
0.001
Log
ic
tran
sist
ors
per
chip
(in
mil
lion
s)
100,000
10,000
1000
100
10
1
0.1
0.01
Prod
ucti
vity
(K)
Tra
ns./S
taff
-M
o.
1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009
IC capacity
productivity
Gap
Design productivity gap
• 1981 leading edge chip required 100 designer months– 10,000 transistors / 100 transistors/month
• 2002 leading edge chip requires 30,000 designer months– 150,000,000 / 5000 transistors/month
• Designer cost increase from $1M to $300M
The mythical man-month• The situation is even worse than the productivity gap indicates• In theory, adding designers to team reduces project completion time• In reality, productivity per designer decreases due to complexities of team
management and communication • In the software community, known as “the mythical man-month” (Brooks
1975)• At some point, can actually lengthen project completion time! (“Too many
cooks”)
10 20 30 400
100002000030000400005000060000
43
24
1916 15 16
18
23
Team
Individual
Months until completion
Number of designers
• 1M transistors, 1 designer=5000 trans/month
• Each additional designer reduces for 100 trans/month
• So 2 designers produce 4900 trans/month each
Summary
• Embedded systems are everywhere
• Key challenge: optimization of design metrics– Design metrics compete with one another
• A unified view of hardware and software is necessary to improve productivity
• Three key technologies– Processor: general-purpose, application-specific,
single-purpose– IC: Full-custom, semi-custom, PLD– Design: Compilation/synthesis, libraries/IP,
test/verification